Botanical Tree Image Generation

Aono, Masaki; Kunii, Tosiyasu L.

doi:10.1109/mcg.1984.276141

Cited by 210 publications

(97 citation statements)

References 19 publications

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“…Bergen et al 1998;Uusitalo and Orland 2001). Even if extremely photorealistic forest scenes may be obtained by combining botanical models of tree architecture with line graphics or real tree textures presented in virtual reality environments (e.g., Aono and Kunii 1984;Honjo and Lim 2001;Fujisaki et al 2008), the tree and branch-level measurements required by these techniques are time-consuming and expensive. Unless tree-wise inventory data are available, the landscapes need to be populated with trees based on less detailed inventory data.…”

Section: Handling Editor: Jean-michel Lebanmentioning

confidence: 99%

Reconstructing forest canopy from the 3D triangulations of airborne laser scanning point data for the visualization and planning of forested landscapes

Ruotsalainen

2017

Annals of Forest Science

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& Key messageWe present a data-driven technique to visualize forest landscapes and simulate their future development according to alternative management scenarios. Gentle harvesting intensities were preferred for maintaining scenic values in a test of eliciting public's preferences based on the simulated landscapes. & Context Visualizations of future forest landscapes according to alternative management scenarios are useful for eliciting stakeholders' preferences on the alternatives. However, conventional computer visualizations require laborious tree-wise measurements or simulators to generate these observations. & Aims We describe and evaluate an alternative approach, in which the visualization is based on reconstructing forest canopy from sparse density, leaf-off airborne laser scanning data. & Methods Computational geometry was employed to generate filtrations, i.e., ordered sets of simplices belonging to the three-dimensional triangulations of the point data. An appropriate degree of filtering was determined by analyzing the topological persistence of the filtrations. The topology was further utilized to simulate changes to canopy biomass, resembling harvests with varying retention levels. Relative priorities of recreational and scenic values of the harvests were estimated based on pairwise comparisons and analytic hierarchy process (AHP). & Results The canopy elements were co-located with the tree stems measured in the field, and the visualizations derived from the entire landscape showed reasonably realistic, despite a low numerical correspondence with plot-level forest attributes. The potential and limitations to improve the proposed parameterization are discussed. & Conclusion Although the criteria to evaluate the landscape visualization and simulation models were not conclusive, the results suggest that forest scenes may be feasibly reconstructed based on data already covering broad areas and readily available for practical applications.

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Section: Handling Editor: Jean-michel Lebanmentioning

confidence: 99%

Reconstructing forest canopy from the 3D triangulations of airborne laser scanning point data for the visualization and planning of forested landscapes

Ruotsalainen

2017

Annals of Forest Science

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“…In the 3-d case, we now consider the branching angle from the 2-d case to be a rotation about the z-axis and add a second rotation about the z-axis. This approach was first taken by ANON AND KUNII (1984). We have forking, main and secondary angles of sizes 30 ~ 70 ~ and 20 ~ respectively.…”

Section: Three-dimensional Drawingmentioning

confidence: 99%

The botanical beauty of random binary trees

Devroye

Kruszewski

1996

Graph Drawing

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ABSTRACT. We present a simple mechanism for quickly rendering computer images of botanical trees based on random binary trees commonly found in computer science. That is, we visualize abstract binary trees as botanical ones. We generate random binary trees by splitting based upon the beta distribution, and obtain the standard binary search trees as a special case. We draw them in PostScript to resemble actual botanical trees found in nature. Through flexible parameterization and extensive randomization, we can produce a rich collection of images.

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“…Examples of stochastic models are: for terrain (Figure 15), 73 fire 74 and flora. 75,76,74,77 To create terrain, Fournier and Fussell 73 takeap arametric patch and add to it a stochastic element. This is done by generating a twodimensional table of values that approximate fractional Brownian motion, and using these values to displace points on the surface patch in a direction perpendicular to the surface.…”

Section: Modelingmentioning

confidence: 99%

“…In as imilar manner,g rass and trees have also been produced with the particle streaks forming the branches and leaves. 77 Aono and Kunii 75 and Smith 76 both used a "grammar" approach to generate procedural models of trees. Theyb oth used a formal language describing the branching patterns of trees devised by biologists whose production rules generate a string representing the branching patterns of a tree.…”

Section: Modelingmentioning

confidence: 99%

Realism in Computer Graphics: A Survey

Amanatides

1987

IEEE Comput. Grap. Appl.

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Botanical Tree Image Generation

Cited by 210 publications

References 19 publications

Reconstructing forest canopy from the 3D triangulations of airborne laser scanning point data for the visualization and planning of forested landscapes

Reconstructing forest canopy from the 3D triangulations of airborne laser scanning point data for the visualization and planning of forested landscapes

The botanical beauty of random binary trees

Realism in Computer Graphics: A Survey

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